糖心TV

Natural Language Processing (NLP) technologies have become increasingly popular to be used to gain insights into unstructured textual data in the finance domain. In this talk, I will present recent developments in NLP for (1) automatic construction of hierarchical topic taxonomy from a large-scale text corpus; (2) named entity recognition and financial event extraction from text; (3) sentiment analysis including sentiment classification, aspect-based sentiment analysis and contrastive opinion extraction; and (4) end-to-end NLP approaches for trading signals prediction. I will conclude my talk with an outlook on potential NLP technologies that will shape the future of FinTech.

The new Consumer Duty significantly extends the FCA鈥檚 regulatory regime targeting retail firms and their supply chain. The extensive new rules recently consulted upon will likely result in significant financial service changes. They signal an important new direction for the FCA, with a strong consumer outcome focus.

The Duty will require significant changes to how firms communicate with their customers, what they need to consider before they do, and how they must track consumer understanding to ensure customers receive better outcomes. It will likely require new and innovative processes and technologies to deliver the new rules, with the changes expected to cost the industry over 拢 2 billion to implement.

The webinar summarises the key components of the new proposals:

路 The scope of the new duty and principle

路 The cross-cutting rules

路 The four outcomes

Exploring the proposals relating to customer communications in greater depth and what this might mean for innovation in the sector.

Using French administrative data, Huan will show that, relative to similar firms taking new bank loans, SMEs that take a FinTech loan borrow 20% more from banks in the next two years. The effect is more pronounced for low-collateral firms and when the FinTech loan finances the acquisition of tangible assets. This is consistent with firms using uncollateralized FinTech loans to acquire assets they can pledge to obtain bank loans. We also find evidence that firms use FinTech loans to meet urgent liquidity needs. In contrast, we find no evidence of a superior screening ability of FinTech lenders.